Sebastian Weichwald | DeepAI

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∙ 06/01/2023

Unfair Utilities and First Steps Towards Improving Them

Many fairness criteria constrain the policy or choice of predictors. In ...

0 Frederik Hytting Jørgensen, et al. ∙

∙ 03/31/2023

Simple Sorting Criteria Help Find the Causal Order in Additive Noise Models

Additive Noise Models (ANM) encode a popular functional assumption that ...

0 Alexander G. Reisach, et al. ∙

∙ 03/11/2022

Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the Past

Instrumental variable (IV) regression relies on instruments to infer cau...

0 Nikolaj Thams, et al. ∙

∙ 02/12/2022

Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning

Questions in causality, control, and reinforcement learning go beyond th...

0 Sebastian Weichwald, et al. ∙

∙ 03/29/2021

Compositional Abstraction Error and a Category of Causal Models

Interventional causal models describe joint distributions over some vari...

0 Eigil F. Rischel, et al. ∙

∙ 02/26/2021

Beware of the Simulated DAG! Varsortability in Additive Noise Models

Additive noise models are a class of causal models in which each variabl...

0 Alexander G. Reisach, et al. ∙

∙ 02/21/2020

Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values

In this article, we describe the algorithms for causal structure learnin...

0 Sebastian Weichwald, et al. ∙

∙ 02/14/2020

Distributional robustness as a guiding principle for causality in cognitive neuroscience

While probabilistic models describe the dependence structure between obs...

0 Sebastian Weichwald, et al. ∙

∙ 06/04/2018

groupICA: Independent component analysis for grouped data

We introduce groupICA, a novel independent component analysis (ICA) algo...

0 Niklas Pfister, et al. ∙

∙ 07/04/2017

Causal Consistency of Structural Equation Models

Complex systems can be modelled at various levels of detail. Ideally, ca...

0 Paul K. Rubenstein, et al. ∙

∙ 05/23/2016

A note on the expected minimum error probability in equientropic channels

While the channel capacity reflects a theoretical upper bound on the ach...

0 Sebastian Weichwald, et al. ∙

∙ 05/02/2016

Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data

Causal inference concerns the identification of cause-effect relationshi...

0 Sebastian Weichwald, et al. ∙

∙ 03/10/2016

Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Optimization on manifolds is a class of methods for optimization of an o...

0 James Townsend, et al. ∙

∙ 12/15/2015

Causal and anti-causal learning in pattern recognition for neuroimaging

Pattern recognition in neuroimaging distinguishes between two types of m...

0 Sebastian Weichwald, et al. ∙

∙ 12/14/2015

Decoding index finger position from EEG using random forests

While invasively recorded brain activity is known to provide detailed in...

0 Sebastian Weichwald, et al. ∙

∙ 12/03/2015

MERLiN: Mixture Effect Recovery in Linear Networks

Causal inference concerns the identification of cause-effect relationshi...

0 Sebastian Weichwald, et al. ∙

∙ 11/15/2015

Causal interpretation rules for encoding and decoding models in neuroimaging

Causal terminology is often introduced in the interpretation of encoding...

0 Sebastian Weichwald, et al. ∙

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